Computer Security

15 papers with code • 1 benchmarks • 1 datasets

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Use these libraries to find Computer Security models and implementations


Most implemented papers

Novel Feature Extraction, Selection and Fusion for Effective Malware Family Classification

ManSoSec/Microsoft-Malware-Challenge 13 Nov 2015

This paradigm is presented and discussed in the present paper, where emphasis has been given to the phases related to the extraction, and selection of a set of novel features for the effective representation of malware samples.

Defending Against Neural Fake News

rowanz/grover NeurIPS 2019

We find that best current discriminators can classify neural fake news from real, human-written, news with 73% accuracy, assuming access to a moderate level of training data.

Reservoir of Diverse Adaptive Learners and Stacking Fast Hoeffding Drift Detection Methods for Evolving Data Streams

alipsgh/tornado 7 Sep 2017

In addition, a number of methods have been developed to detect concept drifts in these streams.

Active Anomaly Detection via Ensembles

shubhomoydas/ad_examples 17 Sep 2018

First, we present an important insight into how anomaly detector ensembles are naturally suited for active learning.

Effectiveness of Tree-based Ensembles for Anomaly Discovery: Insights, Batch and Streaming Active Learning

shubhomoydas/ad_examples 23 Jan 2019

Our results show that active learning allows us to discover significantly more anomalies than state-of-the-art unsupervised baselines, our batch active learning algorithm discovers diverse anomalies, and our algorithms under the streaming-data setup are competitive with the batch setup.

Evaluating Explanation Methods for Deep Learning in Security

alewarne/Layerwise-Relevance-Propagation-for-LSTMs 5 Jun 2019

Deep learning is increasingly used as a building block of security systems.

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

allenai/dolma NA 2021

Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.

Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection

greshake/llm-security 23 Feb 2023

Large Language Models (LLMs) are increasingly being integrated into various applications.

Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection

xiaojunxu/dnn-binary-code-similarity 22 Aug 2017

The problem of cross-platform binary code similarity detection aims at detecting whether two binary functions coming from different platforms are similar or not.

Robust Neural Malware Detection Models for Emulation Sequence Learning

tychen5/sportslottery 28 Jun 2018

These models target the core of the malicious operation by learning the presence and pattern of co-occurrence of malicious event actions from within these sequences.